Exploring Generative Adversarial Networks
In this chapter, we will introduce Generative Adversarial Networks (GANs) and discuss the evolution of this data generation method. You will learn about the typical architecture of a GAN. After this, we will explain its training process and discuss the main challenges. Then, we will highlight various applications of GANs, including generating images and text-to-image translation. Additionally, we will study a practical coding example demonstrating how to use GANs to generate photorealistic images. Finally, we will also discuss variations of GANs, such as conditional GANs, CycleGANs, CTGANs, WGANs, WGAN-GPs, and f-GANs.
In this chapter, we’re going to cover the following main topics:
- What is a GAN?
- Training a GAN
- Utilizing GANs to generate synthetic data
- Hands-on GANs in practice
- Variations of GANs
